BDML Ecommerce
What is Big Data?•    “Big data," is a group of data technologies that    are making the storage, manipulation and    anal...
Big Data Challenge•    Managing the three “V”s of big data    –        Volume    –        Velocity         •   The speed a...
The Business Needs•    Traditionally business wanted answers to Five    Questions•    Traditional BI answers two of those ...
Big Data Opportunity•    The relational databases has limitations    –        Data needs to be modeled    –        Need to...
Value Potential of Big Data                      6
Pattern-Based Strategy Model                      7
Patterns for Competitive       Advantage                    8
Examples: Zara (Retail Clothing)                        9
Major Appliance Retailer                    10
Enterprise Hadoop Solutions Rating Q1 2012                               11
Big Data Opportunities•    McKinsey projects that in the U.S. alone, there will    be a need by 2018 for 140,000 to 190,00...
Big Data Opportunities•    Need for another 1.5 million data-literate    managers    –        Formal training in predictiv...
McKinsey Predicts the Magnitude  of Big Data Potential Across            Sectors                       14
How Big Data is going to change BI  and Analytics – MIT Research                          15
Billion dollar idea                      16
DMA Campaign Response Rates•                                     2010 rate of 3.72% and an    Email to a house list averag...
18
Mobile Marketing and Purchase                     19
Improving Offer Acceptance Rate: Algorithms to                  Personalize Offers•    K-Means Clustering for clustering U...
Logistic Regression for Click         Prediction                       21
How Does The Model Work?–    Classification Algorithms learns from Examples in    a process known as Training–    Need Tra...
Choosing Products for customer and Ordering             Customer              Details                                     ...
Conclusion•    On the basis of our on-line surveys, face-to-    face survey and analysis of studies done by    others we c...
Upcoming SlideShare
Loading in …5
×

Bdml Presentation

671 views

Published on

Published in: Technology, Education
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
671
On SlideShare
0
From Embeds
0
Number of Embeds
230
Actions
Shares
0
Downloads
2
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Bdml Presentation

  1. 1. BDML Ecommerce
  2. 2. What is Big Data?• “Big data," is a group of data technologies that are making the storage, manipulation and analysis of large volumes of data cheaper and faster than ever.• Types of “Big data” – Transactional Data – Data from mobile app • Location data , Profiles 2
  3. 3. Big Data Challenge• Managing the three “V”s of big data – Volume – Velocity • The speed at which data is coming and changing – Variety • Text, Audio, Video• Big Data is mainly unstructured data 3• Technology to store big data
  4. 4. The Business Needs• Traditionally business wanted answers to Five Questions• Traditional BI answers two of those questions – What Happened? – Reports and Ad-hoc Queries – Why it Happened? – Analytics, Cubes• Dash Boards and Score Cards Answer the third – What is happening Now?• 4
  5. 5. Big Data Opportunity• The relational databases has limitations – Data needs to be modeled – Need to know the business needs to create good data models – Data needs to be structured to support queries• Can we do analytics on big data and answer all Five business questions? 5
  6. 6. Value Potential of Big Data 6
  7. 7. Pattern-Based Strategy Model 7
  8. 8. Patterns for Competitive Advantage 8
  9. 9. Examples: Zara (Retail Clothing) 9
  10. 10. Major Appliance Retailer 10
  11. 11. Enterprise Hadoop Solutions Rating Q1 2012 11
  12. 12. Big Data Opportunities• McKinsey projects that in the U.S. alone, there will be a need by 2018 for 140,000 to 190,000 “data scientists”• Steep technical learning curves and a lack of qualified technical staff create barriers to adoption 12
  13. 13. Big Data Opportunities• Need for another 1.5 million data-literate managers – Formal training in predictive analytics and statistics.• The technologies in the big data area are not Analyst Friendly – Need Programmers with knowledge of Hadoop, Statistics and analytics • Companies Retraining programmers and13 database
  14. 14. McKinsey Predicts the Magnitude of Big Data Potential Across Sectors 14
  15. 15. How Big Data is going to change BI and Analytics – MIT Research 15
  16. 16. Billion dollar idea 16
  17. 17. DMA Campaign Response Rates• 2010 rate of 3.72% and an Email to a house list averaged a 19.47% open rate, a 6.64% click-through rate, and a 1.73% conversion rate, with a bounce-back unsubscribe rate of 0.77%.• Direct mail: Letter-sized envelopes had a response rate this year of 3.42% for a house list and 1.38% for a prospect list.• Catalogs had the lowest cost per order of $47.61, just ahead of inserts at $47.69, email at $53.85, and postcards $75.32.• Outbound telemarketing to prospects had the highest cost per order of $309.25, but it also had the highest response rate from prospects of 6.16%.• Paid search had an average cost per click of $3.79, with a 3.81% conversion rate. The conversion rate (after click) of Internet display advertisements was slightly higher at 4.43%. 17
  18. 18. 18
  19. 19. Mobile Marketing and Purchase 19
  20. 20. Improving Offer Acceptance Rate: Algorithms to Personalize Offers• K-Means Clustering for clustering Users – Cluster users based on brand preferences and demographics – Most popular Clustering Algorithm• Logistic regression for finding the probability of accepting an offer• SVD (Single Value Decomposition) to reduce dimensionality of data and to reduce noise – Reducing the dimensions to a few improves performance and reduce accuracy 20
  21. 21. Logistic Regression for Click Prediction 21
  22. 22. How Does The Model Work?– Classification Algorithms learns from Examples in a process known as Training– Need Training Data and Decide on Training Algorithm 22
  23. 23. Choosing Products for customer and Ordering Customer Details Click PredictionSale Items Model for Product Items Display Chosen Order 23
  24. 24. Conclusion• On the basis of our on-line surveys, face-to- face survey and analysis of studies done by others we conclude that the opportunity for a Marketing application based on Big data and Machine Learning is great. In a scale of 1-10 we rate this opportunity at 9 24

×